scholarly journals Time- and Space-Varying Atmospheric Phase Correction in Discontinuous Ground-Based Synthetic Aperture Radar Deformation Monitoring

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3883 ◽  
Author(s):  
Zengshu Huang ◽  
Jinping Sun ◽  
Qing Li ◽  
Weixian Tan ◽  
Pingping Huang ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Microwave Remote Sensing ◽  
Phase Correction ◽  
Deformation Monitoring ◽  
Synthetic Aperture ◽  
Time And Space ◽  
Atmospheric Effect ◽  
Trend Extraction ◽  
Phase Signal ◽  
Aperture Radar

Ground-based synthetic aperture radar (GB-SAR) uses active microwave remote-sensing observation mode to achieve two-dimensional deformation measurement and deformation trend extraction, which shows great prospects in the field of deformation monitoring. However, in the process of GB-SAR deformation monitoring, the disturbances caused by atmospheric effect cannot be neglected, and the atmospheric phases will seriously affect the precision of deformation monitoring. In discontinuous GB-SAR deformation monitoring mode, the atmospheric phases are particularly affected by changes of time and space, so the traditional models of atmospheric phase correction are no longer applicable. In this paper, the interferometric phase signal model considering atmospheric phase is first established. Then, the time- and space-varying characteristics of the atmospheric phase are analyzed, and a novel time- and space-varying atmospheric phase correction algorithm, based on coherent scatterers analysis, is proposed. Finally, slope deformation monitoring experiments are carried out to verify the validity and robustness of the proposed algorithm.

scholarly journals Earth Environmental Monitoring Using Multi-Temporal Synthetic Aperture Radar: A Critical Review of Selected Applications

2021 ◽  
Vol 13 (4) ◽  
pp. 604
Author(s):  
Donato Amitrano ◽  
Gerardo Di Martino ◽  
Raffaella Guida ◽  
Pasquale Iervolino ◽  
Antonio Iodice ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Microwave Remote Sensing ◽  
Radar Data ◽  
Synthetic Aperture ◽  
Special Focus ◽  
Arid Environments ◽  
Synthetic Aperture Radar Data ◽  
Multi Temporal ◽  
Aperture Radar

Microwave remote sensing has widely demonstrated its potential in the continuous monitoring of our rapidly changing planet. This review provides an overview of state-of-the-art methodologies for multi-temporal synthetic aperture radar change detection and its applications to biosphere and hydrosphere monitoring, with special focus on topics like forestry, water resources management in semi-arid environments and floods. The analyzed literature is categorized on the base of the approach adopted and the data exploited and discussed in light of the downstream remote sensing market. The purpose is to highlight the main issues and limitations preventing the diffusion of synthetic aperture radar data in both industrial and multidisciplinary research contexts and the possible solutions for boosting their usage among end-users.

Deformation information extraction method based on differential synthetic aperture radar interferometry

2020 ◽  
Vol 39 (4) ◽  
pp. 5311-5318
Author(s):  
Zhengquan Hu ◽  
Yu Liu ◽  
Xiaowei Niu ◽  
Guoping Lei
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Adaptive Filtering ◽  
Extraction Method ◽  
Deformation Monitoring ◽  
Radar Interferometry ◽  
Synthetic Aperture ◽  
Filtering Method ◽  
Synthetic Aperture Radar Interferometry ◽  
Aperture Radar

As aerospace technology, computer technology, network communication technology and information technology become more and more perfect, a variety of sensors for measurement and remote sensing are constantly emerging, and the ability to acquire remote sensing data is also continuously enhanced. Synthetic Aperture Radar Interferometry (InSAR) technology greatly expands the function and application field of imaging radar. Differential InSAR (DInSAR) developed based on InSAR technology has the advantages of high precision and all-weather compared with traditional measurement methods. However, DInSAR-based deformation monitoring is susceptible to spatiotemporal coherence, orbital errors, atmospheric delays, and elevation errors. Since phase noise is the main error of InSAR, to determine the appropriate filtering parameters, an iterative adaptive filtering method for interferogram is proposed. For the limitation of conventional DInSAR, to improve the accuracy of deformation monitoring as much as possible, this paper proposes a deformation modeling based on ridge estimation and regularization as a constraint condition, and introduces a variance component estimation to optimize the deformation results. The simulation experiment of the iterative adaptive filtering method and the deformation modeling proposed in this paper shows that the deformation information extraction method based on differential synthetic aperture radar has high precision and feasibility.

scholarly journals Long-Term Water Surface Area Monitoring and Derived Water Level Using Synthetic Aperture Radar (SAR) at Altevatn, a Medium-Sized Arctic Lake

2019 ◽  
Vol 11 (23) ◽  
pp. 2780 ◽  
Author(s):  
Hannah Vickers ◽  
Eirik Malnes ◽  
Kjell-Arild Høgda
Keyword(s):  
Synthetic Aperture Radar ◽  
Water Level ◽  
Lake Water ◽  
Clustering Algorithm ◽  
Independent Solution ◽  
Microwave Remote Sensing ◽  
Synthetic Aperture ◽  
Arctic Lake ◽  
Water Cover ◽  
Aperture Radar

Monitoring water storage in lakes and reservoirs is critical to water resource management, especially in a changing climate. Satellite microwave remote sensing offers a weather and light-independent solution for mapping water cover over large scales. We have used 13 years of synthetic aperture radar (SAR) data from three different sensors (Sentinel-1, RADARSAT-2, and Envisat advanced synthetic aperture radar (ASAR)) to develop a method for mapping surface water cover and thereby estimating the lake water extent (LWE). The method uses the unsupervised K-means clustering algorithm together with specific post-processing techniques to create binary maps of the water area. We have specifically tested and validated the method at Altevatn, a medium-sized arctic lake in Northern Norway, by using in-situ measurements of the water level. The multi-sensor SAR LWE time series were used in conjunction with the water level measurements to derive the lake hypsometry while at the same time quantifying the accuracy of our method. For Altevatn lake we estimated LWE with a root mean squared error (RMSE) of 0.89 km2 or 1.4% of the mean LWE, while the inferred lake water level (LWL) was associated with an RMSE of 0.40 m, or 2.5% of the maximum annual variation. We foresee that there is potential to further develop the algorithm by generalizing its use to other lakes worldwide and automating the process such that near real-time monitoring of LWE may be possible.

Speckle processing method for synthetic-aperture-radar phase correction

1989 ◽  
Vol 14 (1) ◽  
pp. 1 ◽  
Author(s):  
P. H. Eichel ◽  
D. C. Ghiglia ◽  
C. V. Jakowatz
Keyword(s):  
Synthetic Aperture Radar ◽  
Phase Correction ◽  
Processing Method ◽  
Synthetic Aperture ◽  
Aperture Radar

scholarly journals EVALUATION OF DATA APPLICABILITY FOR D-INSAR IN AREAS COVERED BY ABUNDANT VEGETATION

2018 ◽  
Vol XLII-3 ◽  
pp. 2277-2281
Author(s):  
P. Zhang ◽  
Z. Zhao
Keyword(s):  
Synthetic Aperture Radar ◽  
Surface Deformation ◽  
Deformation Monitoring ◽  
Guizhou Province ◽  
Synthetic Aperture ◽  
Economic Losses ◽  
Large Area ◽  
Disaster Assessment ◽  
Evaluation Of Data ◽  
Aperture Radar

In the past few years, the frequent geological disasters have caused enormous casualties and economic losses. Therefore, D-InSAR (differential interferometry synthetic aperture radar) has been widely used in early-warning and post disaster assessment. However, large area of decorrelation often occurs in the areas covered with abundant vegetation, which seriously affects the accuracy of surface deformation monitoring. In this paper, we analysed the effect of sensor parameters and external environment parameters on special decorrelation. Then Synthetic Aperture Radar (SAR) datasets acquired by X-band TerraSAR-X, Phased Array type L-band Synthetic Aperture Satellite-2 (ALOS-2), and C-band Sentinel-1 in Guizhou province were collected and analysed to generate the maps of coherence, which were used to evaluating the applicability of datasets of different wavelengths for D-InSAR in forest area. Finally, we found that datasets acquired by ALOS-2 had the best monitoring effect.

scholarly journals A SHORT REVIEW ON PERSISTENT SCATTERER INTERFEROMETRY TECHNIQUES FOR SURFACE DEFORMATION MONITORING

2022 ◽  
Vol XLVI-4/W3-2021 ◽  
pp. 23-31
Author(s):  
A. M. H. Ansar ◽  
A. H. M. Din ◽  
A. S. A. Latip ◽  
M. N. M. Reba
Keyword(s):  
Synthetic Aperture Radar ◽  
Surface Deformation ◽  
Deformation Monitoring ◽  
Synthetic Aperture ◽  
Structural Development ◽  
Interferometric Synthetic Aperture Radar ◽  
Persistent Scatterer Interferometry ◽  
Persistent Scatterers ◽  
Persistent Scatterer ◽  
Aperture Radar

Abstract. Technology advancement has urged the development of Interferometric Synthetic Aperture Radar (InSAR) to be upgraded and transformed. The main contribution of the InSAR technique is that the surface deformation changes measurements can achieve up to millimetre level precision. Environmental problems such as landslides, volcanoes, earthquakes, excessive underground water production, and other phenomena can cause the earth's surface deformation. Deformation monitoring of a surface is vital as unexpected movement, and future behaviour can be detected and predicted. InSAR time series analysis, known as Persistent Scatterer Interferometry (PSI), has become an essential tool for measuring surface deformation. Therefore, this study provides a review of the PSI techniques used to measure surface deformation changes. An overview of surface deformation and the basic principles of the four techniques that have been developed from the improvement of Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR), which is Small Baseline Subset (SBAS), Stanford Method for Persistent Scatterers (StaMPS), SqueeSAR and Quasi Persistent Scatterer (QPS) were summarised to perceive the ability of these techniques in monitoring surface deformation. This study also emphasises the effectiveness and restrictions of each developed technique and how they suit Malaysia conditions and environment. The future outlook for Malaysia in realising the PSI techniques for structural monitoring also discussed in this review. Finally, this review will lead to the implementation of appropriate techniques and better preparation for the country's structural development.

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